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I have a decade of experience as a software engineer, but little quantitative finance knowledge. I have an idea for a simple trading strategy based around moving averages. In order to test it, I'd like to benchmark the algorithm against historical data sets for some publicly traded US tickers.

My question is mostly around the mechanical act of actually doing this.

Where can I obtain these data sets? Either in downloaded files, or via web API?

Ideally, these would be free. I don't need high resolution or any special features. Basically just a daily quote for some major US companies, tabulated nicely into a CSV or some other structured data. Actually, a simple flat file download would be preferable, as I don't want to be hammering some API and incurring latency, limits, and/or potential cost.

Thanks!

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Recently I came across interesting platform. https://www.quantopian.com/

they offer exactly what you need and for free. Basically, you code your algo in python, they provide data using api and backtesting.
Hope it helps.

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    $\begingroup$ Add quantconnect to the answer as well - they even offer tick data which quantopian doesnt. $\endgroup$
    – novice
    Commented Sep 6, 2016 at 2:50
  • $\begingroup$ as I understand it, quantopian only provides data for the stocks and they working on futures $\endgroup$
    – chester89
    Commented Oct 18, 2016 at 9:27
  • $\begingroup$ This link gives a 404 . . . out of business I guess. $\endgroup$
    – Vic F
    Commented Dec 29, 2022 at 4:08
  • $\begingroup$ They got acquired by data.nasdaq.com -- the API works still pretty much the same $\endgroup$ Commented Jan 4, 2023 at 9:09
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If you are by any chance familiar with R take a look at the following post LINK

It offers an easy way to obtain data from Yahoo finance, Google etc.

Cheers.

PS: Jameson, I am in a similar situation as you are. I was digging a bit deeper a found also Quandl

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I have used https://www.tickdata.com/ and https://www.quantgo.com/ I enjoy the simplistic nature of obtaining data that they use, so for someone new to quantitative finance like you, I recommend that you try them. https://www.quandl.com also have excellent quality data, easy to use APIs

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If you are just looking for basic intraday data (open, high, low, close, and volume data), you can check out Alpha Vantage. File can either be in json or csv format. They provide 500 API requests per day. If you require a higher API volume limit and technical support, you need to sign up for their premium membership. Another API-based data vendor is IEX Cloud which has a free plan with a limit of 50,000 core messages per month and only 5 years worth of data. For institutional quality data, there's algoseek for US listed and delisted stocks from January 2007 with over 50 fully customizable minute bars and TickData which can provide historical data from all US Exchanges since January 1993 but can be quite expensive.

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EDIT: Hi, I'm incredibly sorry. I'm archiving tendollardata.com and chartsonlygoup.com (link), as of April 1, 2021. All data will only be up to December 31, 2020. I feel compelled to be on a new mission now (link). All orders should have been refunded already. Quant StackExchange is the only place I've advertised my sites.

There are many (hundreds?) of ways to get historical equity data online, both free and paid. Check out the "What data sources are available online?" megathread: What data sources are available online?

I have my own data service I just started, https://tendollardata.com, that I really do think is worth checking. I write out why in that thread (https://quant.stackexchange.com/a/61220/34362).

Basically, I wanted to make a cheap service for hobbyists/non-full-time analysts. And I really do think it achieves those goals.

I have data used on chartsonlygoup.com, so you can judge for yourself (e.g. https://chartsonlygoup.com/tsla).

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You can find exactly what you have described at algoseek.com. Check their 'Primary Exchange Daily OHLC' (advanced) or 'Standard Daily OHLC' (basic) dataset. Both provide daily bars and differ by the number of data fields. They provide historical data back to 2007 with flexible delivery options and multiple data formats support (including csv and parquet)

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